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Temperature Sensing Using Wireless Passive Contactless Air-Filled Substrate-Integrated Waveguide (CLAF-SIW)

2021· article· en· W3193962072 on OpenAlexaff
Amirmasoud Amirkabiri, Dawn Idoko, Gregory Bridges, Behzad Kordi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsLinearityMaterials scienceDielectricRepeatabilitySubstrate (aquarium)OptoelectronicsWaveguideW bandAir gap (plumbing)Sensitivity (control systems)Frequency bandRadio frequencyTemperature measurementWirelessElectronic engineeringElectrical engineeringAntenna (radio)Computer scienceEngineeringTelecommunicationsPhysicsChemistry

Abstract

fetched live from OpenAlex

In this paper, a high quality factor contactless air-filled substrate-integrated waveguide (CLAF-SIW) for temperature sensing is presented and experimentally tested. The resonant frequency of the CLAF-SIW sensor is determined by the dielectric constant of the electromagnetic bandgap (EBG) substrate and the dimensions of the structure where both parameters are temperature-dependent. As a result, the resonant frequency of the CLAF-SIW sensor changes with temperature. The temperature sensing behaviour of the structure and its linearity and repeatability was verified by experiments. A sensitivity of 311.5 kHz/°C was achieved and its linearity shows that the sensor is a viable candidate for wireless passive temperature sensing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.211
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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